Digital predistortion (DPD) technique is widely used to linearize a radio frequency power amplifier (PA). It is the fastest and cost effective digital processing technique to moderate the distortions in PA caused by nonlinearity and memory effects. Digital predistorter is inverse of the PA, so the design of a digital predistorter requires the accurate identification of PA’s behavior. This paper...

This paper describes the design and implementation of a memoryless digital predistortion (DPD) system for the linearization of power amplifiers. The system prototype predistorter requirements and architecture are implemented over a DSP-FPGA development kit. The design methodology is described in practical blocks and analyzed in detail with special emphasis in the digital domain, where the algor...

power amplifiers (pas) are inherently nonlinear elements and digital predistortion is a highly cost-effective approach to linearize them. although most existing architectures assume that the pa has a memoryless nonlinearity, memory effects of the pas in many applications ,such as wideband code-division multiple access (wcdma) or orthogonal frequency-division multiplexing (ofdm), can no longer b...

To gratify the requirements of modern wireless communication, linearization of power amplifier (PA) becomes a foremost research field. Several linearization techniques have been introduced time to time. Digital pre-distortion linearization technique is the best linearization technique from other linearization techniques. In this paper, modified memory polynomial function is used to model PA and...

This paper presents an adaptive Digital Predistorter (DPD) to handle the nonlinearity and memory challenges that effect transmitted signal in High Power Amplifier (HPA) system. The proposed scheme first handles by estimating reverse error, then obtained is processed FIR filter diminish effect. simulation results of method present a superior performance compared with state-of-the-art methods use...

This paper demonstrates an unprecedented novel neural network (NN)-based digital predistortion (DPD) solution to overcome the signal impairments and nonlinearities in Analog Optical fronthauls using radio over fiber (RoF) systems. DPD is realized with Volterra-based procedures that utilize indirect learning architecture (ILA) direct (DLA) becomes quite complex. The proposed method NNs evades is...

This paper introduces a recursive algorithm of Kalman filter for digital predistorter parameters extraction based on memory polynomials predistorter model. The predistorter model is firstly formulated as linear regression expression. Then we derive the state-space equation of the model and attain the steps of the algorithm. Finally, the accuracy and stability of the algorithm is proved by simul...

Digital subscriber line (DSL) systems transport high-bandwidth data, such as multimedia, to service subscribers over ordinary twisted pair copper wire telephone lines. One of the important components of the DSL system is the line driver (LD) or the power amplifier (PA). The linearity of the LD is crucial to have a high-speed internet. Any non-linearity in the LD will create intermodulation dist...

While digital predistortion (DPD) usually targets only the linearity performance of radio–frequency (RF) power amplifier (PA), this work addresses more than a single PA metric exploiting multi-objective optimization approach. We present predistorer learning procedure based on constrained algorithm that maximizes RF output power, while guaranteeing prescribed level, i.e., maximum normalized mean...

Power amplifiers (PAs) are inherently nonlinear elements and digital predistortion is a highly cost-effective approach to linearize them. Although most existing architectures assume that the PA has a memoryless nonlinearity, memory effects of the PAs in many applications ,such as wideband code-division multiple access (WCDMA) or orthogonal frequency-division multiplexing (OFDM), can no longer b...